Vitamin D and mortality: meta-analysis of individual participant data from a large consortium of cohort studies from Europe and the United States

Objective: To investigate the association between serum 25-hydroxyvitamin D concentrations (25(OH)D) and mortality in a large consortium of cohort studies paying particular attention to potential age, sex, season, and country differences.

Design: Meta-analysis of individual participant data of eight prospective cohort studies from Europe and the US.

Setting: General population.

Participants: 26 018 men and women aged 50-79 years

Main outcome measures: All-cause, cardiovascular, and cancer mortality.

Results: 25(OH)D concentrations varied strongly by season (higher in summer), country (higher in US and northern Europe) and sex (higher in men), but no consistent trend with age was observed. During follow-up, 6695 study participants died, among whom 2624 died of cardiovascular diseases and 2227 died of cancer. For each cohort and analysis, 25(OH)D quintiles were defined with cohort and subgroup specific cut-off values. Comparing bottom versus top quintiles resulted in a pooled risk ratio of 1.57 (95% CI 1.36 to 1.81) for all-cause mortality. Risk ratios for cardiovascular mortality were similar in magnitude to that for all-cause mortality in subjects both with and without a history of cardiovascular disease at baseline. With respect to cancer mortality, an association was only observed among subjects with a history of cancer (risk ratio, 1.70 (1.00 to 2.88)). Analyses using all quintiles suggest curvilinear, inverse, dose-response curves for the aforementioned relationships. No strong age, sex, season, or country specific differences were detected. Heterogeneity was low in most meta-analyses.

Conclusions: Despite levels of 25(OH)D strongly varying with country, sex, and season, the association between 25(OH)D level and all-cause and cause-specific mortality was remarkably consistent. Results from a long term randomised controlled trial addressing longevity are being awaited before vitamin D supplementation can be recommended in most individuals with low 25(OH)D levels.

Depression and mortality: Artifact of measurement and analysis?

Background: Previous research demonstrates various associations between depression, cardiovascular disease (CVD) incidence and mortality, possibly as a result of the different methodologies used to measure depression and analyse relationships. This analysis investigated the association between depression, CVD incidence (CVDI) and mortality from CVD (MCVD), smoking related conditions (MSRC), and all causes (MALL), in a sample data set, where depression was measured using items from a validated questionnaire and using items derived from the factor analysis of a larger questionnaire, and analyses were conducted based on continuous data and grouped data.

Methods: Data from the PRIME Study (N=9798 men) on depression and 10-year CVD incidence and mortality were analysed using Cox proportional hazards models.

Results: Using continuous data, both measures of depression resulted in the emergence of positive associations between depression and mortality (MCVD, MSRC, MALL). Using grouped data, however, associations between a validated measure of depression and MCVD, and between a measure of depression derived from factor analysis and all measures of mortality were lost.

Limitations: Low levels of depression, low numbers of individuals with high depression and low numbers of outcome events may limit these analyses, but levels are usual for the population studied.

Conclusions: These data demonstrate a possible association between depression and mortality but detecting this association is dependent on the measurement used and method of analysis. Different findings based on methodology present clear problems for the elucidation and determination of relationships. The differences here argue for the use of validated scales where possible and suggest against over-reduction via factor analysis and grouping.

Comparing the decline in coronary heart disease and stroke mortality in neighbouring countries with different healthcare systems

Objective
To examine age and gender specific trends in coronary heart disease (CHD) and stroke mortality in two neighbouring countries, the Republic of Ireland (ROI) and Northern Ireland (NI). Design Epidemiological study of time trends in CHD and stroke mortality.

Setting/patients
The populations of the ROI and NI, 1985–2010.

Interventions
None.

Main outcome measures
Directly age standardised CHD and stroke mortality rates were calculated and analysed using joinpoint regression to identify years where the slope of the linear trend changed significantly. This was performed separately for specific age groups (25–54, 55–64, 65–74 and 75–84 years) and by gender. Annual percentage change (APC) and 95% CIs are presented.

Results
There was a striking similarity between the two countries, with percentage change between 1985 and 1989 and between 2006 and 2010 of 67% and 69% in
CHD mortality, and 64% and 62% in stroke mortality for the ROI and NI, respectively. However, joinpoint analysis identified differences in the pace of change between the two countries. There was an accelerated pace of decline (negative APC) in mortality for both CHD and stroke in both countries from the mid-1990s (APC ROI −8% (95% CI −9.5 to 6.5) and NI −6.6% (−6.9 to −6.3)), but the accelerated decrease started later for CHD mortality in the ROI. In recent years, a levelling off in CHD mortality was observed in the 25–54 year age group in NI and in stroke mortality for men and women in the ROI.

Conclusions
While differences in the pace of change in mortality were observed at different time points, similar, substantial decreases in CHD and stroke mortality were achieved between 1985 and 1989 and between 2006 and 2010 in the ROI and NI despite important differences in health service structures. There is evidence of a levelling in mortality rates in some groups in recent years.

Is Mortality Spatial or Social?

Mortality modelling for the purposes of demographic forecasting and actuarial pricing is generally done at an aggregate level using national data. Modelling at this level fails to capture the variation in mortality within country and potentially leads to a mis-specification of mortality forecasts for a subset of the population. This can have detrimental effects for pricing and reserving in the actuarial context. In this paper we consider mortality rates at a regional level and analyse the variation in those rates. We consider whether variation in mortality rates within a country can be explained using local economic and social variables. Using Northern Ireland data on mortality and measures of deprivation we identify the variables explaining mortality variation. We create a population polarisation variable and find that this variable is significant in explaining some of the variation in mortality rates. Further, we consider whether spatial and non-spatial models have a part to play in explaining mortality differentials.

The influence of parents, older siblings, and non-parental care on infant development at nine months of age

Background: The majority of research examining the influence of social environment on early child development suggests benefits to two-parent households, but contradictory evidence for the effects of siblings. The aims of the present study were to examine the influence of the child's proximal social environment, and the effects of interactions between socioeconomic status and social environment on developmental outcomes.

Methods: Primary caregivers of a representative sample of 10,748 nine-month-old infants in Ireland completed the Ages and Stages Questionnaire and provided information on social environment. Adjustment was made for infant and maternal characteristics, household income, and area where the child was living at the time of the study. Further analyses tested for interactions between social environment and household income.

Results: Binary logistic regressions indicated no effects for number of parents in the household. However, the presence of siblings in the household was a consistent predictor of failing to reach milestones in communication, gross motor, problem-solving, and personal-social development. Furthermore, there was a gradient of increasing likelihood of failing in gross motor, problem-solving, and personal-social development with increasing numbers of siblings. Care by a grandparent decreased the likelihood of failing in communication and personal-social development.

Conclusions:These findings do not support the majority of research that finds positive benefits for two-parent households. Similarly, the findings suggest limited effects for non-parental care. However, the observed negative effects of siblings support both the confluence and resource dilution models of sibling effect. Examination of follow-up data may elucidate current findings.

Parents' experiences of caring for their infant following surgery in the neonatal period: A literature review

Previous research with parents of preterm and low-birth weight infants admitted to the Neonatal Intensive Care Unit (NICU) has indicated the following: (i) parents are at risk of experiencing stress associated with the NICU environment; (ii) parents are at risk of short- and longer-term psychological distress; and (iii) the family is at risk of longer-term stress and strain. However, parents of infants admitted to the NICU for surgery are an under-researched population. This paper provides an overview of the current literature in relation to this issue. The results highlight the paucity of research conducted with parents of infants admitted to the NICU for surgery. A number of gaps and limitations were also identified in the current literature, including a lack of examination why some parents cope better than others, and a focus solely on parents of preterm and low birth weight infants. To conclude, further research with parents of infants who had surgery in the first few weeks of life is needed. Such information could help inform clinicians caring for these infants and their families, and would enable identification of those parents and families most at risk.

Structural Breaks in Mortality Models and their Consequences

In recent years, the issue of life expectancy has become of upmost importance to pension providers, insurance companies and the government bodies in the developed world. Significant and consistent improvements in mortality rates and, hence, life expectancy have led to unprecedented increases in the cost of providing for older ages. This has resulted in an explosion of stochastic mortality models forecasting trends in mortality data in order to anticipate future life expectancy and, hence, quantify the costs of providing for future aging populations. Many stochastic models of mortality rates identify linear trends in mortality rates by time, age and cohort, and forecast these trends into the future using standard statistical methods. The modeling approaches used failed to capture the effects of any structural change in the trend and, thus, potentially produced incorrect forecasts of future mortality rates. In this paper, we look at a range of leading stochastic models of mortality and test for structural breaks in the trend time series.

Regional variation in five indicators of health in early childhood: a cohort study

Background Persistent and marked differences in adult morbidity and mortality between regions in the United Kingdom (UK) are often referred to as the north-south gradient (or divide) and the Scottish effect, and are only partly explained by adult levels of socioeconomic status (SES) or risk factors which suggests variation arising earlier in life. The aim of the current study was to examine regional variations in five health indicators in children in England and Scotland at birth and three years of age.
Methods Respondents were 10,500 biological Caucasian mothers of singleton children recruited to the Millennium Cohort Study (MCS). Outcome variables were: gestational age and weight at birth, and height, body mass index (BMI), and externalising behaviour at age three. Region/Country was categorised as: South (reference), Midlands, North, and Scotland. Respondents provided information on child, maternal, household, and socioeconomic characteristics when the cohort infant/child was aged nine months and again when aged three years. 
Results There were no significant regional variations for gestational age or birthweight. However, at age three there was a north-south gradient for externalising behaviour and a north-south divide in BMI which attenuated on adjustment. However, a north-south divide in height was not fully explained by the adjusted model. There was also evidence of a ‘Midlands effect’, with increased likelihoods of shorter stature and behaviour problems. Results showed a Scottish effect for height and BMI in the unadjusted models, and height in the adjusted model. However, Scottish children were less likely to show behaviour problems in crude and adjusted models. 
Conclusions Findings indicated no marked regional differences in children at birth, but by age three some regional health differences were evident, and though not distinct north-south gradients or Scottish effects, are evidence of health inequalities appearing at an early age and dependent on geographic location.

Identifying Structural Breaks in Stochastic Mortality Models

In recent years, the issue of life expectancy has become of utmost importance to pension providers, insurance companies, and government bodies in the developed world. Significant and consistent improvements in mortality rates and hence life expectancy have led to unprecedented increases in the cost of providing for older ages. This has resulted in an explosion of stochastic mortality models forecasting trends in mortality data to anticipate future life expectancy and hence quantify the costs of providing for future aging populations. Many stochastic models of mortality rates identify linear trends in mortality rates by time, age, and cohort and forecast these trends into the future by using standard statistical methods. These approaches rely on the assumption that structural breaks in the trend do not exist or do not have a significant impact on the mortality forecasts. Recent literature has started to question this assumption. In this paper, we carry out a comprehensive investigation of the presence or of structural breaks in a selection of leading mortality models. We find that structural breaks are present in the majority of cases. In particular, we find that allowing for structural break, where present, improves the forecast result significantly.

Repeated measures of body mass index and C-reactive protein in relation to all-cause mortality and cardiovascular disease: Results from the consortium on health and ageing network of cohorts in Europe and the United States (CHANCES)

Obesity has been linked with elevated levels of C-reactive protein (CRP), and both have been associated with increased risk of mortality and cardiovascular disease (CVD). Previous studies have used a single ‘baseline’ measurement and such analyses cannot account for possible changes in these which may lead to a biased estimation of risk. Using four cohorts from CHANCES which had repeated measures in participants 50 years and older, multivariate time-dependent Cox proportional hazards was used to estimate hazard ratios (HR) and 95 % confidence intervals (CI) to examine the relationship between body mass index (BMI) and CRP with all-cause mortality and CVD. Being overweight (≥25–<30 kg/m2) or moderately obese (≥30–<35) tended to be associated with a lower risk of mortality compared to normal (≥18.5–<25): ESTHER, HR (95 % CI) 0.69 (0.58–0.82) and 0.78 (0.63–0.97); Rotterdam, 0.86 (0.79–0.94) and 0.80 (0.72–0.89). A similar relationship was found, but only for overweight in Glostrup, HR (95 % CI) 0.88 (0.76–1.02); and moderately obese in Tromsø, HR (95 % CI) 0.79 (0.62–1.01). Associations were not evident between repeated measures of BMI and CVD. Conversely, increasing CRP concentrations, measured on more than one occasion, were associated with an increasing risk of mortality and CVD. Being overweight or moderately obese is associated with a lower risk of mortality, while CRP, independent of BMI, is positively associated with mortality and CVD risk. If inflammation links CRP and BMI, they may participate in distinct/independent pathways. Accounting for independent changes in risk factors over time may be crucial for unveiling their effects on mortality and disease morbidity.

Models of Mortality - Analysing the Residuals

The area of mortality modelling has received significant attention over the last 20 years owing to the need to quantify and forecast improving mortality rates. This need is driven primarily by the concern of governments, professionals, insurance and actuarial professionals and individuals to be able to fund their old age. In particular, to quantify the costs of increasing longevity we need suitable model of mortality rates that capture the dynamics of the data and forecast them with sufficient accuracy to make them useful. In this paper we test several of those models by considering the fitting quality and in particular, testing the residuals of those models for normality properties. In a wide ranging study considering 30 countries we find that almost exclusively the residuals do not demonstrate normality. Further, in Hurst tests of the residuals we find evidence that structure remains that is not captured by the models.